In PIV, particle images are correlated to obtain vector displacement information. Since the particle images themselves are random functions, the resulting correlation functions have random components which create a finite probability of having erroneous measurements which must be removed before the dataset can be used.
Main features:
- provide an interactive display to view PIV vector fields for analysis
- develop manual vector cleanup software that does not fatigue the user
- develop automated (mathematical) algorithms for vector cleanup that are robust
- make a flexible system that can operate on PIV datasets from all types of flow fields
- create batch processing capability to cleanup large numbers of vector fields
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